code: def get_mask_loss(self, sdf_output, network_object_mask, object_mask):
      mask = ~(network_object_mask & object_mask)
      if mask.sum() == 0:
          return torch.tensor(0.0).cuda().float()
      sdf_pred = -self.alpha * sdf_output[mask]
      gt = object_mask[mask].float()
      mask_loss = (
          (1 / self.alpha)
          * F.binary_cross_entropy_with_logits(
              sdf_pred.squeeze(), gt, reduction="sum"
          )
          / float(object_mask.shape[0])
      )
      return mask_loss
  
file_path: insightface/reconstruction/PBIDR/code/model/loss.py
imports: import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 4 for calling the IFLoss obj's underlying member method code with example usage: obj.get_mask_loss(sdf_output, network_object_mask, object_mask) and returns: mask_loss, torch